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Using genetic algorithms to optimize social robot behavior for improved pedestrian flow

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2 Author(s)
Eldridge, B.D. ; Dept. of Electr. & Comput. Eng., Colorado State Univ., Fort Collins, CO, USA ; Maciejewski, A.A.

This paper expands on previous research on the effect of introducing social robots into crowded situations in order to improve pedestrian flow. In this case, a genetic algorithm is applied to find the optimal parameters for the interaction model between the robots and the people. Preliminary results indicate that adding social robots to a crowded situation can result in significant improvement in pedestrian flow. Using the optimized values of the model parameters as a guide, these robots can be designed to be more effective at improving the pedestrian flow. While this work only applies to one situation, the technique presented can be applied to a wide variety of scenarios.

Published in:

Systems, Man and Cybernetics, 2005 IEEE International Conference on  (Volume:1 )

Date of Conference:

10-12 Oct. 2005

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